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A Coagulation-Related Gene-Based Prognostic Model for Invasive Ductal Carcinoma
Frontiers in Genetics ( IF 3.7 ) Pub Date : 2021-09-21 , DOI: 10.3389/fgene.2021.722992
Jing Li 1 , Jiajia Du 1 , Yanhong Wang 2 , Hongyan Jia 1
Affiliation  

Background: Invasive ductal carcinoma (IDC) is the most common type of metastatic breast cancer. Due to the lack of valuable molecular biomarkers, the diagnosis and prognosis of IDC remain a challenge. A large number of studies have confirmed that coagulation is positively correlated with angiogenesis-related factors in metastatic breast cancer. Therefore, the purpose of this study was to construct a COAGULATION-related genes signature for IDC using the bioinformatics approaches.

Methods: The 50 hallmark gene sets were obtained from the molecular signature database (MsigDB) to conduct Gene Set Variation Analysis (GSVA). Gene Set Enrichment Analysis (GSEA) was applied to analyze the enrichment of HALLMARK_COAGULATION. The COAGULATION-related genes were extracted from the gene set. Then, Limma Package was used to identify the differentially expressed COAGULATION-related genes (DECGs) between ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) samples in GSE26340 data set. A total of 740 IDC samples from The Cancer Genome Atlas (TCGA) database were divided into a training set and a validation set (7:3). The univariate and multivariate Cox regression analyses were performed to construct a risk signature, which divided the IDC samples into the high- and low-risk groups. The overall survival (OS) curve and receiver operating characteristic (ROC) curve were drawn in both training set and validation set. Finally, a nomogram was constructed to predict the 1-, 2-, 3-, 4-, and 5-year survival rates of IDC patients. Quantitative real-time fluorescence PCR (qRT-PCR) was performed to verify the expression levels of the prognostic genes.

Results: The “HALLMARK_COAGULATION” was significantly activated in IDC. There was a significant difference in the clinicopathological parameters between the DCIS and IDC patients. Twenty-four DECGs were identified, of which five genes (SERPINA1, CAPN2, HMGCS2, MMP7, and PLAT) were screened to construct the prognostic model. The high-risk group showed a significantly lower survival rate than the low-risk group both in the training set and validation set (p=3.5943e-06 and p=0.014243). The risk score was demonstrated to be an independent predictor of IDC prognosis. A nomogram including risk score, pathological_stage, and pathological_N provided a quantitative method to predict the survival probability of 1-, 2-, 3-, 4-, and 5-year in IDC patients. The results of decision curve analysis (DCA) further demonstrated that the nomogram had a high potential for clinical utility.

Conclusion: This study established a COAGULATION-related gene signature and showed its prognostic value in IDC through a comprehensive bioinformatics analysis, which may provide a potential new prognostic mean for patients with IDC.



中文翻译:

基于凝血相关基因的浸润性导管癌预后模型

背景:浸润性导管癌 (IDC) 是最常见的转移性乳腺癌类型。由于缺乏有价值的分子生物标志物,IDC的诊断和预后仍然是一个挑战。大量研究证实,在转移性乳腺癌中,凝血与血管生成相关因子呈正相关。因此,本研究的目的是使用生物信息学方法构建 IDC 的凝血相关基因特征。

方法:从分子特征数据库 (MsigDB) 中获得 50 个标志性基因集以进行基因集变异分析 (GSVA)。应用基因集富集分析(GSEA)来分析HALLMARK_COAGULATION的富集。COAGULATION 相关基因是从基因组中提取的。然后,使用 Limma Package 鉴定导管癌之间差异表达的 COAGULATION 相关基因 (DECGs)就地(DCIS) 和 GSE26340 数据集中的浸润性导管癌 (IDC) 样本。来自癌症基因组图谱(TCGA)数据库的 740 个 IDC 样本被分为训练集和验证集(7:3)。执行单变量和多变量 Cox 回归分析以构建风险特征,将 IDC 样本分为高风险组和低风险组。在训练集和验证集中绘制总生存 (OS) 曲线和受试者工作特征 (ROC) 曲线。最后,构建列线图来预测 IDC 患者的 1、2、3、4 和 5 年生存率。进行定量实时荧光 PCR (qRT-PCR) 以验证预后基因的表达水平。

结果:“HALLMARK_COAGULATION”在IDC中被显着激活。DCIS 和 IDC 患者之间的临床病理参数存在显着差异。鉴定出 24 个 DECG,其中 5 个基因(SERPINA1, CAPN2, HMGCS2, MMP7, 和 平台) 被筛选以构建预后模型。高风险组在训练集和验证集上的存活率均显着低于低风险组(=3.5943e-06 和 =0.014243)。风险评分被证明是 IDC 预后的独立预测因子。包括风险评分、pathological_stage 和 pathological_N 的列线图提供了一种定量方法来预测 IDC 患者 1、2、3、4 和 5 年的生存概率。决策曲线分析 (DCA) 的结果进一步表明,列线图具有很高的临床应用潜力。

结论: 本研究建立了一个 COAGULATION 相关基因特征,并通过全面的生物信息学分析显示了其在 IDC 中的预后价值,这可能为 IDC 患者提供潜在的新预后手段。

更新日期:2021-09-21
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